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Simulated maximum likelihood estimation of demand systems with corner solutions and panel data application to industrial energy demand
[Estimation par maximum de vraisemblance simulé de systèmes de demande avec solutions en coin et données de panel application à la demande d’énergie industrielle]

Author

Listed:
  • Raja Chakir

    (GREMAQ - Groupe de recherche en économie mathématique et quantitative - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique)

  • Alban Thomas

    (LEERNA - Laboratoire d'Economie de l'Environnement et des Ressources Naturelles - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - INRA - Institut National de la Recherche Agronomique)

Abstract

his paper proposes a convenient method for evaluating energy price elasticities, when firms may switch between energy regimes. The methodology involves estimation of an energy demand system that explicitly deals with the zero expenditures problem, while allowing for unobserved heterogeneity. We apply a Simulated Maximum Likelihood technique for estimating a simultaneous equation energy demand system in the French pulp and paper sector, over the period 1983-1996. Endogenous regime transitions are accounted for when computing energy price elasticities. Our estimates are used to predict the outcome of an environmental policy aimed at reducing CO 2 emissions in the paper and pulp industry.

Suggested Citation

  • Raja Chakir & Alban Thomas, 2003. "Simulated maximum likelihood estimation of demand systems with corner solutions and panel data application to industrial energy demand [Estimation par maximum de vraisemblance simulé de systèmes de," Post-Print hal-05136019, HAL.
    • Handle: RePEc:hal:journl:hal-05136019
    DOI: 10.3917/redp.136.0773
    as

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